A non-invasive diagnostic nomogram for CHB-related early cirrhosis: a prospective study.

This study aimed to construct a non-invasive diagnostic nomogram based on high-frequency ultrasound and magnetic resonance imaging results for early liver cirrhosis patients with chronic hepatitis B (CHB) which cannot be detected by conventional non-invasive examination methods but can only be diagnosed through invasive liver puncture for pathological examination. 72 patients with CHB were enrolled in this prospective study, and divided into S4 stage of liver cirrhosis and S0-S3 stage of non-liver cirrhosis according to pathological findings. Binary logistic regression analysis was performed to identify independent predictors, and a diagnostic nomogram was constructed for CHB-related early cirrhosis. It was validated and calibrated by bootstrap self-extraction. Binary logistic regression analysis showed that age (OR 1.14, 95% CI (1.04-1.27)), right hepatic vein diameter (OR 0.43, 95% CI 0.23-0.82), presence or absence of nodules (OR 31.98, 95% CI 3.84-266.08), and hepatic parenchymal echogenicity grading (OR 12.82, 95% CI 2.12-77.51) were identified as independent predictive indicators. The nomogram based on the 4 factors above showed good performance, with a sensitivity and specificity of 90.70% and 89.66%, respectively. The area under the curve (AUC) of the prediction model was 0.96, and the predictive model showed better predictive performance than APRI score (AUC 0.57), FIB-4 score (AUC 0.64), INPR score (AUC 0.63), and LSM score (AUC 0.67). The calibration curve of the prediction model fit well with the ideal curve, and the decision curve analysis showed that the net benefit of the model was significant. The nomogram in this study can detect liver cirrhosis in most CHB patients without liver biopsy, providing a direct, fast, and accurate practical diagnostic tool for clinical doctors.

Physiological network approach to prognosis in cirrhosis: A shifting paradigm.

Decompensated liver disease is complicated by multi-organ failure and poor prognosis. The prognosis of patients with liver failure often dictates clinical management. Current prognostic models have focused on biomarkers considered as individual isolated units. Network physiology assesses the interactions among multiple physiological systems in health and disease irrespective of anatomical connectivity and defines the influence or dependence of one organ system on another. Indeed, recent applications of network mapping methods to patient data have shown improved prediction of response to therapy or prognosis in cirrhosis. Initially, different physical markers have been used to assess physiological coupling in cirrhosis including heart rate variability, heart rate turbulence, and skin temperature variability measures. Further, the parenclitic network analysis was recently applied showing that organ systems connectivity is impaired in patients with decompensated cirrhosis and can predict mortality in cirrhosis independent of current prognostic models while also providing valuable insights into the associated pathological pathways. Moreover, network mapping also predicts response to intravenous albumin in patients hospitalized with decompensated cirrhosis. Thus, this review highlights the importance of evaluating decompensated cirrhosis through the network physiologic prism. It emphasizes the limitations of current prognostic models and the values of network physiologic techniques in cirrhosis.

Serum dithiothreitol-oxidizing capacity (DOC) is a promising biomarker for excluding significant liver fibrosis: a proof-of-concept study.

BACKGROUND: APRI and FIB-4 scores are used to exclude clinically significant fibrosis (defined as stage ≥ F2) in patients with chronic viral hepatitis. However, the cut-offs for these scores (generated by Youden indices) vary between different patient cohorts. This study aimed to evaluate whether serum dithiothreitol-oxidizing capacity (DOC), i.e., a surrogate test of quiescin sulfhydryl oxidase-1, which is a matrix remodeling enzyme, could be used to non-invasively identify significant fibrosis in patients with various chronic liver diseases (CLDs). METHODS: Diagnostic performance of DOC was compared with APRI and FIB-4 for identifying significant fibrosis. ROC curve analyses were undertaken in: a) two chronic hepatitis B (CHB) cohorts, independently established from hospitals in Wenzhou (n = 208) and Hefei (n = 120); b) a MASLD cohort from Wenzhou hospital (n = 122); and c) a cohort with multiple CLD etiologies (except CHB and MASLD; n = 102), which was identified from patients in both hospitals. Cut-offs were calculated using the Youden index. All CLD patients (n = 552) were then stratified by age for ROC curve analyses and cut-off calculations. RESULTS: Stratified by CLD etiology or age, ROC curve analyses consistently showed that the DOC test was superior to APRI and FIB-4 for discriminating between clinically significant fibrosis and no fibrosis, when APRI and FIB-4 showed poor/modest diagnostic performance (P < 0.05, P < 0.01 and P < 0.001 in 3, 1 and 3 cohort comparisons, respectively). Conversely, the DOC test was equivalent to APRI and FIB-4 when all tests showed moderate/adequate diagnostic performances (P > 0.05 in 11 cohort comparisons). DOC had a significant advantage over APRI or FIB-4 scores for establishing a uniform cut-off independently of age and CLD etiology (coefficients of variation of DOC, APRI and FIB-4 cut-offs were 1.7%, 22.9% and 47.6% in cohorts stratified by CLD etiology, 2.0%, 26.7% and 29.5% in cohorts stratified by age, respectively). The uniform cut-off was 2.13, yielded from all patients examined. Surprisingly, the uniform cut-off was the same as the DOC upper limit of normal with a specificity of 99%, estimated from 275 healthy control individuals. Hence, the uniform cut-off should possess a high negative predictive value for excluding significant fibrosis in primary care settings. A high DOC cut-off with 97.5% specificity could be used for detecting significant fibrosis (≥ F2) with an acceptable positive predictive value (87.1%). CONCLUSIONS: This proof-of-concept study suggests that the DOC test may efficiently rule out and rule in significant liver fibrosis, thereby reducing the numbers of unnecessary liver biopsies. Moreover, the DOC test may be helpful for clinicians to exclude significant liver fibrosis in the general population.

Establishment of diagnostic model and identification of diagnostic markers between liver cancer and cirrhosis based on multi-chip and machine learning.

OBJECTIVE: Most cases of hepatocellular carcinoma (HCC) arise as a consequence of cirrhosis. In this study, our objective is to construct a comprehensive diagnostic model that investigates the diagnostic markers distinguishing between cirrhosis and HCC. METHODS: Based on multiple GEO datasets containing cirrhosis and HCC samples, we used lasso regression, random forest (RF)-recursive feature elimination (RFE) and receiver operator characteristic analysis to screen for characteristic genes. Subsequently, we integrated these genes into a multivariable logistic regression model and validated the linear prediction scores in both training and validation cohorts. The ssGSEA algorithm was used to estimate the fraction of infiltrating immune cells in the samples. Finally, molecular typing for patients with cirrhosis was performed using the CCP algorithm. RESULTS: The study identified 137 differentially expressed genes (DEGs) and selected five significant genes (CXCL14, CAP2, FCN2, CCBE1 and UBE2C) to construct a diagnostic model. In both the training and validation cohorts, the model exhibited an area under the curve (AUC) greater than 0.9 and a kappa value of approximately 0.9. Additionally, the calibration curve demonstrated excellent concordance between observed and predicted incidence rates. Comparatively, HCC displayed overall downregulation of infiltrating immune cells compared to cirrhosis. Notably, CCBE1 showed strong correlations with the tumour immune microenvironment as well as genes associated with cell death and cellular ageing processes. Furthermore, cirrhosis subtypes with high linear predictive scores were enriched in multiple cancer-related pathways. CONCLUSION: In conclusion, we successfully identified diagnostic markers distinguishing between cirrhosis and hepatocellular carcinoma and developed a novel diagnostic model for discriminating the two conditions. CCBE1 might exert a pivotal role in regulating the tumour microenvironment, cell death and senescence.

[Research progress on detection techniques for effective albumin concentration].

Hypoalbuminemia is one of the important clinical features of decompensated cirrhosis. As the disease progresses, not only does the total albumin concentration decrease, but so does the proportion of albumin that remains structurally and functionally intact. The structural and functional integrity of albumin is essential for its normal physiological role in the body. This led to the concept of "effective albumin concentration," which may be much lower than the total albumin concentration routinely measured clinically in patients with advanced cirrhosis. Liquid chromatography-tandem mass spectrometry, and electron paramagnetic resonance (EMR) are emerging technologies for effective albumin concentration detection, showing promising clinical application prospects, but research in patients with cirrhosis is still in the preliminary stage. Therefore, this article will comprehensively summarize the latest research on the aspects of effective albumin detection methods, liquid chromatography-tandem mass spectrometry, and electron paramagnetic resonance, as well as their applications.

[Interpretation of the 2024 American Diabetes Association guidelines for the comprehensive management of non-alcoholic fatty liver disease combined with diabetes mellitus].

Non-alcoholic fatty liver disease (NAFLD) is a common concomitant disease in adults with type 2 diabetes mellitus (T2DM) and prediabetes. Therefore, T2DM/NAFLD patient populations are at high risk for cardiovascular disease. The occurrence and progression of non-alcoholic fatty liver disease-related liver fibrosis and cardiovascular disease have a severe impact on the patient's prognosis and mortality rate. The American Diabetes Association's 2024 "Guidelines for the Standardized Management of Diabetes" put forward recommendations relevant to the screening, evaluation, treatment, and management of NAFLD in T2DM and prediabetic populations, as well as liver fibrosis. The important measures for decelerating liver inflammation and fibrosis progression and the risk of cardiovascular disease are based on improvements in lifestyle methods, weight loss, and blood sugar control.

[Pay attention to the diagnosis and treatment of "easily neglected" complications in liver cirrhosis].

Managing cirrhosis complications is an important measure for improving patients' clinical outcomes. Therefore, in order to provide a complete disease assessment and comprehensive treatment, improve quality of life, and improve the prognosis for patients with cirrhosis, it is necessary to pay attention to complications such as thrombocytopenia and portal vein thrombosis in addition to common or severe complications such as ascites, esophagogastric variceal bleeding, hepatic encephalopathy, and hepatorenal syndrome. The relevant concept that an effective albumin concentration is more helpful in predicting the cirrhosis outcome is gradually being accepted; however, the detection method still needs further standardization and commercialization.

[Development of a grading diagnostic model for schistosomiasis-induced liver fibrosis based on radiomics and clinical laboratory indicators].

OBJECTIVE: To investigate the feasibility of developing a grading diagnostic model for schistosomiasis-induced liver fibrosis based on B-mode ultrasonographic images and clinical laboratory indicators. METHODS: Ultrasound images and clinical laboratory testing data were captured from schistosomiasis patients admitted to the Second People's Hospital of Duchang County, Jiangxi Province from 2018 to 2022. Patients with grade I schistosomiasis-induced liver fibrosis were enrolled in Group 1, and patients with grade II and III schistosomiasis-induced liver fibrosis were enrolled in Group 2. The machine learning binary classification tasks were created based on patients'radiomics and clinical laboratory data from 2018 to 2021 as the training set, and patients'radiomics and clinical laboratory data in 2022 as the validation set. The features of ultrasonographic images were labeled with the ITK-SNAP software, and the features of ultrasonographic images were extracted using the Python 3.7 package and PyRadiomics toolkit. The difference in the features of ultrasonographic images was compared between groups with t test or Mann-Whitney U test, and the key imaging features were selected with the least absolute shrinkage and selection operator (LASSO) regression algorithm. Four machine learning models were created using the Scikit-learn repository, including the support vector machine (SVM), random forest (RF), linear regression (LR) and extreme gradient boosting (XGBoost). The optimal machine learning model was screened with the receiver operating characteristic curve (ROC), and features with the greatest contributions to the differentiation features of ultrasound images in machine learning models with the SHapley Additive exPlanations (SHAP) method. RESULTS: The ultrasonographic imaging data and clinical laboratory testing data from 491 schistosomiasis patients from 2019 to 2022 were included in the study, and a total of 851 radiomics features and 54 clinical laboratory indicators were captured. Following statistical tests (t = -5.98 to 4.80, U = 6 550 to 20 994, all P values < 0.05) and screening of key features with LASSO regression, 44 features or indicators were included for the subsequent modeling. The areas under ROC curve (AUCs) were 0.763 and 0.611 for the training and validation sets of the SVM model based on clinical laboratory indicators, 0.951 and 0.892 for the training and validation sets of the SVM model based on radiomics, and 0.960 and 0.913 for the training and validation sets of the multimodal SVM model. The 10 greatest contributing features or indicators in machine learning models included 2 clinical laboratory indicators and 8 radiomics features. CONCLUSIONS: The multimodal machine learning models created based on ultrasound-based radiomics and clinical laboratory indicators are feasible for intelligent identification of schistosomiasis-induced liver fibrosis, and are effective to improve the classification effect of one-class data models.

Advancing hepatic recompensation: Baveno VII criteria and therapeutic innovations in liver cirrhosis management.

The Baveno VII criteria redefine the management of decompensated liver cirrhosis, introducing the concept of hepatic recompensation marking a significant departure from the conventional view of irreversible decline. Central to this concept is addressing the underlying cause of cirrhosis through tailored therapies, including antivirals and lifestyle modifications. Studies on alcohol, hepatitis C virus, and hepatitis B virus-related cirrhosis demonstrate the efficacy of these interventions in improving liver function and patient outcomes. Transjugular intrahepatic portosystemic shunt (TIPS) emerges as a promising intervention, effectively resolving complications of portal hypertension and facilitating recompensation. However, optimal timing and patient selection for TIPS remain unresolved. Despite challenges, TIPS offers renewed hope for hepatic recompensation, marking a significant advancement in cirrhosis management. Further research is needed to refine its implementation and maximize its benefits. In conclusion, TIPS stands as a promising avenue for improving hepatic function and patient outcomes in decompensated liver cirrhosis within the framework of the Baveno VII criteria.

Screening for metabolic dysfunction-associated fatty liver disease: Time to discard the emperor's clothes of normal liver enzymes?

Metabolic dysfunction-associated fatty liver disease (MAFLD) is the most prevalent chronic liver condition worldwide. Current liver enzyme-based screening methods have limitations that may missed diagnoses and treatment delays. Regarding Chen et al, the risk of developing MAFLD remains elevated even when alanine aminotransferase levels fall within the normal range. Therefore, there is an urgent need for advanced diagnostic techniques and updated algorithms to enhance the accuracy of MAFLD diagnosis and enable early intervention. This paper proposes two potential screening methods for identifying individuals who may be at risk of developing MAFLD: Lowering these thresholds and promoting the use of noninvasive liver fibrosis scores.

Evaluation of Mac-2 binding protein glycosylation isomer (M2BPGi) as a diagnostic marker for staging liver fibrosis: a meta-analysis.

Objective: This study aimed to assess the accuracy of Mac-2 binding protein glycosylation isomer (M2BPGi) in predicting the stage of liver fibrosis. Methods: Articles published until October 10, 2023, were searched in the PubMed, Embase, Web of Science, and Cochrane Library databases. Pooled sensitivity, specificity, diagnostic odds ratio (DOR), summary receiver-operator curves (SROC), and Spearman's rank correlation coefficient were used to examine the accuracy of M2BPGi in predicting the stage of liver fibrosis. A 95% confidence interval (CI) was provided for each estimate. Results: Twenty-four studies were included in this meta-analysis, including 3,839 patients with liver fibrosis, 409 of whom progressed to stage 4 or above. The pooled sensitivity, specificity, and area under the ROC (AUC) for M2BPGi predicting liver fibrosis ≥F3 were 0.74 (95% CI [0.65-0.82]), 0.84 (95% CI [0.76-0.89]), and 14.99 (95% CI [9.28-24.21]), respectively. The pooled sensitivity, specificity, and AUC for ≥F4 were 0.80 (95% CI [0.70-0.88]), 0.80 (95% CI [0.73-0.86]), and 16.43 (95% CI [0.84-0.90]), respectively. Conclusion: Among different sample partitions, M2BPGi has the best diagnostic performance for liver fibrosis stage ≥4. Furthermore, the cutoff of 1-2 is more accurate than that of 0-1 or 2-3 for fibrosis ≥ F3 and ≥ F4. Registration: CRD42023483260.

Noninvasive Assessment of Portal Hypertension.

The progressive use of noninvasive tests (NITs) has changed the way hepatologists diagnose and manage patients with chronic liver disease, mainly because of their easiness to use and the ability to be repeated during follow-up. Liver stiffness measurement is the NIT with more scientific evidence. NITs have demonstrated to be useful to detect not only liver fibrosis but also the presence of clinically significant portal hypertension. Moreover, current evidence supports they can also be useful to evaluate the prognosis of patients with chronic liver disease.

The non-invasive serum biomarkers contributes to indicate liver fibrosis staging and evaluate the progress of chronic hepatitis B.

BACKGROUND: This study aimed to evaluate the diagnostic abilities of the non-invasive serum biomarkers to predict liver fibrosis staging and evaluate the progress of hepatitis B. METHODS: We enrolled 433 patients with chronic HBV infection had complete medical data available for the study, who underwent percutaneous liver biopsy. The extent of fibrosis was assessed using the modified METAVIR score. The predictive values of the non-invasive serum biomarkers were evaluated by the areas under the receiving operator characteristics curves (AUROCs) with 95% confidence intervals. RESULTS: The proportion of males with progressive stages of liver fibrosis was relatively larger, and the average age of patients with cirrhosis stages is older than the non-cirrhotic stages. We found PLT, GGT, ALP, TB, FIB4 and GPR to be significantly associated with liver fibrosis in our cohort. GGT showed a sensitivity of 71.4% and specificity of 76.7% in distinguishing cirrhosis (F4) from non-cirrhotic stages (F1-3), with an AUROC of 0.775 (95%CI 0.711-0.840).The AUROCs of the GPR in distinguishing cirrhosis (F4) from non-cirrhotic stages (F1-3) was 0.794 (95%CI 0.734-0.853), but it had a lower sensitivity of 59.2%. Additionally, GGT, FIB4, and GPR could differentiate advanced fibrosis (F3-4) from non-advanced fibrosis (F1-2) among individuals with chronic hepatitis B, with AUROCs of 0.723 (95%CI 0.668-0.777), 0.729 (95%CI 0.675-0.782), and 0.760 (95%CI: 0.709-0.811) respectively. CONCLUSIONS: GGT was a better biomarker to distinguish cirrhosis (F4) from non-cirrhotic stages (F1-3), while GPR was a better biomarker to identify advanced fibrosis (F3-4) and non-advanced fibrosis (F1-2) in patients with chronic hepatitis B.

3D-Printed SERS Chips for Highly Specific Detection of Denatured Type I and IV Collagens in Blood for Early Hepatic Fibrosis Diagnosis.

Hepatic fibrosis, the insidious progression of chronic liver scarring leading to life-threatening cirrhosis and hepatocellular carcinoma, necessitates the urgent development of noninvasive and precise diagnostic methodologies. Denatured collagen emerges as a critical biomarker in the pathogenesis of hepatic fibrosis. Herein, we have for the first time developed 3D-printed collagen capture chips for highly specific surface-enhanced Raman scattering (SERS) detection of denatured type I and type IV collagen in blood, facilitating the early diagnosis of hepatic fibrosis. Employing a novel blend of denatured collagen-targeting peptide-modified silver nanoparticle probes (Ag@DCTP) and polyethylene glycol diacrylate (PEGDA), we engineered a robust ink for the 3D fabrication of these collagen capture chips. The chips are further equipped with specialized SERS peptide probes, Ag@ICTP@R1 (S-I) and Ag@IVCTP@R2 (S-IV), tailored for the targeted detection of type I and IV collagen, respectively. The SERS chip platform demonstrated exceptional specificity and sensitivity in capturing and detecting denatured type I and IV collagen, achieving detection limits of 3.5 ng/mL for type I and 3.2 ng/mL for type IV collagen within a 10-400 ng/mL range. When tested on serum samples from hepatic fibrosis mouse models across a spectrum of fibrosis stages (S0-S4), the chips consistently measured denatured type I collagen and detected a progressive increase in type IV collagen concentration, which correlated with the severity of fibrosis. This novel strategy establishes a benchmark for the multiplexed detection of collagen biomarkers, enhancing our capacity to assess the stages of hepatic fibrosis.

Relationships of serum MMP-7 and clinical characteristics in choledochal cyst children.

BACKGROUND: Matrix metalloproteinase-7 (MMP-7) is associated with biliary injury. This study aimed to evaluate the relationships of serum MMP-7 with clinical characteristics in choledochal cysts (CDC) children. METHODS: Between June 2020 and July 2022, we conducted a prospective study of CDCs who underwent one-stage definitive operation at our center. Serum MMP-7 was measured using an enzyme-linked immunosorbent assay. We evaluated the relationships between serum MMP-7 and age, laboratory tests, imaging examinations, liver fibrosis, MMP-7 expression, and perforation. RESULTS: A total of 328 CDCs were enrolled in the study, with a median serum MMP-7 of 7.67 ng/mL. Higher serum MMP-7 was correlated with younger age at diagnosis (p < 0.001), larger cyst sizes (p < 0.001), higher liver fibrosis stages (p < 0.001), and higher incidence of perforation (p < 0.01). Liver MMP-7 was mainly expressed in intrahepatic and extrahepatic biliary epithelial cells. The area under the receiver operating characteristic curve (AUROC) was 0.630 (p < 0.001) for serum MMP-7 in predicting perforation. When serum MMP-7 was combined with γ-glutamyl transferase (GGT), the AUROC increased to 0.706 (p < 0.001). CONCLUSIONS: Serum MMP-7 was associated with biliary obstruction in CDCs. Patients with high serum MMP-7 were more likely to have severe liver damage and biliary injury, with higher incidences of liver fibrosis and perforation.

Clinical significance of serum Ck18-M65 and M30 levels in patients with chronic hepatitis B combined with nonalcoholic steatohepatitis and liver fibrosis.

In this study, we aimed to explore the clinical significance of serum CK18-M65 and CK18-M30 levels in patients with chronic hepatitis B (CHB) complicated by nonalcoholic steatohepatitis (NASH) and liver fibrosis. The observation and control groups comprised 133 patients with CHB complicated by NASH and 50 healthy patients from our hospital, respectively. Liver function indices, including alanine aminotransferase, glutamic aminotransferase, γ-glutamyltransferase, total bilirubin, total protein, and total cholesterol, were determined using an automatic biochemical analyzer. Hyaluronic acid, type III procollagen, type IV collagen, laminin, and CK18-M65 and M30 levels were detected using ELISA. Serum CK18-M65 and M30 levels in patients with CHB complicated by NASH were positively correlated with the liver fibrosis stage (P < .05). While serum CK18-M65 demonstrated a low diagnostic value for liver fibrosis in the S0-1 stage, it exhibited good diagnostic value for S2-3 stage liver fibrosis. Serum CK18-M30 displayed good diagnostic value for S0-1 and S2-3 hepatic fibrosis, particularly for S2-3 hepatic fibrosis. Elevated serum CK18-M65 and CK18-M30 levels in patients with CHB complicated with NASH suggest their potential utility in evaluating the progression of liver fibrosis in this population. In particular, CK18-M30 exhibits superior diagnostic efficiency.

Monomeric C-reactive protein is associated with severity and prognosis of decompensated hepatitis B cirrhosis.

C-reactive protein (CRP) is an acute-phase protein produced by the liver in response to infection and during chronic inflammatory disorders. Systemic inflammation is a major driver of cirrhosis progression from the compensated to the decompensated stage. Previous studies have shown that pentameric CRP (pCRP) to be a weak predictor of disease severity and prognosis in patients with decompensated hepatitis B cirrhosis, with it being only helpful for identifying patients with a higher short-term risk of death under certain conditions. Accumulating evidence indicates that pCRP dissociates to and acts primarily as the monomeric conformation (mCRP) at inflammatory loci, suggesting that mCRP may be a potentially superior disease marker with higher specificity and relevance to pathogenesis. However, it is unknown whether mCRP and anti-mCRP autoantibodies are associated with disease severity, or progression in decompensated hepatitis B cirrhosis. In this study, we evaluated the serum levels of mCRP and anti-mCRP autoantibodies in patients with decompensated cirrhosis of hepatitis B and their association with disease severity and theoretical prognosis. The results showed that patients with high mCRP and anti-mCRP autoantibody levels had more severe liver damage and that coagulation function was worse in patients with high anti-mCRP autoantibodies. Analysis of the correlation between pCRP, mCRP and anti-mCRP autoantibody levels with Model for End-Stage Liver Disease (MELD), Albumin-Bilirubin (ALBI), and Child-Turcotte-Pugh (CTP) prognostic scores showed that mCRP was the most strongly correlated with MELD score, followed by anti-mCRP autoantibodies; conversely, pCRP was not significantly correlated with prognostic score. Therefore, mCRP and anti-mCRP autoantibodies may be more advantageous clinical indicators than pCRP for evaluating the pathological state of decompensated hepatitis B cirrhosis.

Hematological ratios in patients with acute decompensation and acute-on-chronic liver failure: prognostic factors.

BACKGROUND AND AIMS: Acute-on-chronic liver failure (ACLF) is the most severe form of acutely decompensated cirrhosis and is characterized by the presence of intense systemic inflammation. Leucocyte quantification can serve as an indirect indicator of systemic inflammation. In our study, we investigated the predictive value of hematological ratios (neutrophils to lymphocytes, monocyte to lymphocytes, platelets to lymphocytes, lymphocytes to C-reactive protein, and neutrophils to lymphocytes and platelets) in acute decompensation (AD) and ACLF patients and their relation to disease severity and early mortality. PATIENTS AND METHODS: We included 60 patients with ACLF and AD, and 30 cirrhotic controls. Clinical data were collected, and survival was followed for 1 and 6 months. Blood samples were analyzed at admission for differential leucocytes and assessed for liver and renal function tests. The leukocyte ratios were calculated and compared, and their correlation with liver function indicators and prognosis was assessed. RESULTS: All ratios were significantly higher in AD and ACLF patients compared to control (except for lymphocyte to C-reactive protein ratio which was significantly lower), and were positively correlated with Child-Pugh score, model for end-stage liver disease (MELD)-Na, and ACLF severity scores. Multivariate regression revealed that neutrophil to lymphocyte ratio, monocyte to lymphocyte ratio, and MELD-Na were independent prognostic factors of 1-month and 6-month mortality. A unique prognostic nomogram incorporating MELD-Na, neutrophil to lymphocyte ratio, and monocyte to lymphocyte ratio could be proposed for predicting prognosis in AD and ACLF patients. CONCLUSIONS: Cheap, easy, and noninvasive hematological ratios are introduced as a tool for early identification and risk stratification of AD and ACLF patients.

Development and validation of a new prognostic model for patients with acute-on-chronic liver failure in intensive care unit.

BACKGROUND: Cirrhotic patients with acute-on-chronic liver failure (ACLF) in the intensive care unit (ICU) have a poor but variable prognoses. Accurate prognosis evaluation can guide the rational management of patients with ACLF. However, existing prognostic scores for ACLF in the ICU environment lack sufficient accuracy. AIM: To develop a new prognostic model for patients with ACLF in ICU. METHODS: Data from 938 ACLF patients in the Medical Information Mart for Intensive Care (MIMIC) database were used to develop a new prognostic model (MIMIC ACLF) for ACLF. Discrimination, calibration and clinical utility of MIMIC ACLF were assessed by area under receiver operating characteristic curve (AUROC), calibration curve and decision curve analysis (DCA), respectively. MIMIC ACLF was then externally validated in a multiple-center cohort, the Electronic Intensive Care Collaborative Research Database and a single-center cohort from the Second Hospital of Hebei Medical University in China. RESULTS: The MIMIC ACLF score was determined using nine variables: ln (age) × 2.2 + ln (white blood cell count) × 0.22 - ln (mean arterial pressure) × 2.7 + respiratory failure × 0.6 + renal failure × 0.51 + cerebral failure × 0.31 + ln (total bilirubin) × 0.44 + ln (internationalized normal ratio) × 0.59 + ln (serum potassium) × 0.59. In MIMIC cohort, the AUROC (0.81/0.79) for MIMIC ACLF for 28/90-day ACLF mortality were significantly greater than those of Chronic Liver Failure Consortium ACLF (0.76/0.74), Model for End-stage Liver Disease (MELD; 0.73/0.71) and MELD-Na (0.72/0.70) (all P < 0.001). The consistency between actual and predicted 28/90-day survival rates of patients according to MIMIC ACLF score was excellent and superior to that of existing scores. The net benefit of MIMIC ACLF was greater than that achieved using existing scores within the 50% threshold probability. The superior predictive accuracy and clinical utility of MIMIC ACLF were validated in the external cohorts. CONCLUSION: We developed and validated a new prognostic model with satisfactory accuracy for cirrhotic patients with ACLF hospitalized in the ICU. The model-based risk stratification and online calculator might facilitate the rational management of patients with ACLF.